Aboveground Dry Matter Research Articles

Multi-objective optimization of farmland water level and nitrogen fertilization management for winter wheat cultivation under waterlogging conditions based on TOPSIS-Entropy

Aiming at the problems of reduced winter wheat yield and aggravation of nitrogen leaching pollution caused by the waterlogging in the Middle-Lower Yangtze Plain, China, a two-year field experiment with three farmland water levels (W40, W60, W80) and three nitrogen application rates (N150, N225, N300) as well as a non-waterlogged treatment (CK) was carried out, to investigate the coupling effects of farmland water level and nitrogen application rate on the plant growth, grain yield, crop water productivity (WPC) and nitrogen load with waterlogging conditions. Three man-made waterlogging events were applied at winter wheat jointing-booting stage, heading-flowering stage and grain filling stage, respectively. The results indicated that with the farmland water level decreased from −40 cm to −60 cm and the nitrogen application rate increased from 150 kg∙ha−1 to 225 kg∙ha−1, the plant height, aboveground dry matter, leaf area index, spike length, grain yield, effective panicles, grain number per ear, 1000-grain weight and WPC in the waterlogging field increased significantly. However, since the nitrogen application rate exceeded 225 kg∙ha−1 and farmland water level lowered more than −60 cm, the favorable effects of nitrogen application rate and farmland water level for winter wheat growth and production reduced. Additionally, both the nitrogen load and partial factor productivity of nitrogen (PFPN) increased with the decline of farmland water level, while the nitrogen load increased and the PFPN decreased with the increasing nitrogen application rate. The raise of nitrogen rate from 150 kg∙ha−1 to 225 kg∙ha−1 was beneficial to plant growth, however, the increase of nitrogen application resulted in the decrease of PFPN and increase of drainage nitrogen loads. Compared with the water farmland water level of −40 cm and nitrogen application rate of 150 kg∙ha−1, the increase of nitrogen application rate and the decrease of farmland water level in the range of 50%-100% resulted in yield raise by 5.78%-32.29% approximately and the increase of nitrogen load by 36.20%-178.44% approximately. The comprehensive evaluation with TOPSIS-Entropy method for plant growth, grain yield, WPC, PFPN and nitrogen loads suggested that, the appropriate nitrogen application rate for winter wheat in the waterlogging areas of Middle-Lower Yangtze Plain in China was 225 kg∙ha−1, and the proper farmland water level was lowering to −80 cm in wet year and −60 cm in dry year within 3 days after waterlogging.

Sunflower Growth and Grain Yield under Different Tillage Systems and Sources of Organic Manure on Contrasting Soil Types in Limpopo Province of South Africa

A field study was conducted to assess the effect of tillage systems (TSs) and manure rates (MRs) on sunflower growth and yield at the University of Limpopo Experimental Farm (Syferkuil) which is on sandy loam soils and University of Venda Experimental Farm (UNIVEN) clayey soils, both located in Limpopo Province of South Africa for 2021/2022 and 2022/2023 cropping seasons. The experimental design was a split plot with three replications. The main plot was the tillage treatments: conventional (CON) and in-field rainwater harvesting (IRWH), while the subplots were the manure treatments: viz. poultry and cattle manures at rates of 20 and 35 t ha−10, plus a control (no manure application). The IRWH is a tillage technique that collects rainwater on a 2 m wide runoff strip into the 1 m wide basin where it infiltrates deep into the soil beyond the evaporation zone but is available for crop use. The results revealed that at Syferkuil IRWH had a significant increase (p < 0.05) on grain yield, head diameter, head dry matter and aboveground dry matter yield in both cropping seasons, whereas at UNIVEN, the significant increase was obtained on grain yield, head diameter, aboveground dry matter, plant height and stem girth during both cropping seasons. The effect of manure rate significantly increased with the application rate, with poultry manure at the highest rate of 35 t ha−1 significantly recording high mean values of grain yield, head diameter, head dry matter, aboveground dry matter, plant height and stem girth at both sites during the two cropping seasons. The increase in leaf area index and 100 seed weight by IRWH and manure rate application varied across the growing stages and cropping seasons with no consistent trend. At Syferkuil, TS and MR interaction was significant on head diameter and on aboveground dry matter at flowering stage in the first cropping season, whereas at UNIVEN, it was significant on head diameter in the first cropping season. Therefore, these results suggest that IRWH combined with poultry manure (35 t ha−1) can be adopted to improve sunflower crop yield under similar management and environmental conditions. In the absence of poultry manure, farmers may opt to use cattle manure at a rate of 35 t ha−1 for better improved yield.

Prediction Models of Growth Characteristics and Yield for Chinese Winter Wheat Based on Machine Learning

In order to eliminate the limitations of traditional winter wheat yield prediction methods, the prediction models based on machine learning are used to improve the accuracy of winter wheat yield prediction. In this study, by collecting a large amount of domestic literature about wheat growth characteristics, the irrigation amount, fertilization amount, soil nutrient status, planting density, maximum leaf area index (LAImax), maximum aboveground dry matter accumulation (Dmax) and yield (Y) were chosen to develop the learning models. Using the data of the irrigation amount, fertilization amount, soil nutrient status and planting density as the training set, the regression prediction models (Gaussian process regression mode, linear regression model, regression tree mode and support vector machine model) were used to train and learn the data of the LAImax, Dmax and Y, respectively. The results show that the Gaussian regression model has the best precision compared to the other models. The coefficients of determination (R2) of the learning results of the Gaussian regression model for the LAImax, Dmax and Y are 0.9, 0.93 and 0.86, and the root mean square error (RMSE) is 0.57, 1125.1 and 640.41. Based on the data of the irrigation amount, nitrogen application amount, potassium application amount, phosphorus application amount, organic matter content, total nitrogen content, alkali-hydrolyzable nitrogen content, available phosphorus content, available potassium content and planting density, the method proposed in this paper can reliably predict the LAImax, the Dmax and Y of winter wheat. The results also have certain reference significance for the yield prediction of other crops.

Effect of Soil Water and Nutrient Uptake on Nitrogen Use Efficiency, and Yield of Winter Wheat

The application of nitrogen (N) improves the winter wheat yield. Excessive N application affects winter wheat yields, leading to low net incomes and negative environmental impacts, therefore, optimizing N application is essential. In this study, the effects of N rates on crop growth yield, net income (NI), water use efficiency (WUE), and nitrogen use efficiency (NUE) in the irrigated districts of the eastern loess plateau, China, were investigated using seven N application rates (N0, N90, N180, N210, N240, N270, and N300 kg ha−1) during the 2016–2017 and 2017–2018 seasons. N application significantly increased the total water consumption at 0–200 cm during the growth period, the aboveground dry matter at maturity, the grain nitrogen accumulation, yield, NI, and WUE. However, N exceeding 240 kg ha−1 did not favor dry matter and nitrogen accumulation or translocation from the anthesis stage to the maturity stage, thus leading to reduced yield, NI, and WUE. The transpiration rate and stomatal conductance N240 was highest 21–28 day after anthesis, at 187–276 kg ha−1, which can achieve a high yield and profitability with relatively low environmental costs.

Yield response and water productivity of soybean (Glycine max L.) to deficit irrigation and sowing time in south-eastern Australia

The aim of this study was to investigate irrigation strategies and sowing dates that would maximise soybean yield and water productivity. It is based on field experiments conducted during two seasons and simulation modelling. Irrigation treatments were 33%, 66%, 66% plus 100% during pod development and pod-fill stages, and 100% of crop evapotranspiration (ETc). In the first season experiment, cvs. Bidgee and Snowy were sown on 15 Nov. In the second season, cv. Bidgee was sown on 15 Nov and 15 Dec. Five sowing dates (1, 15, 30 Nov and 15, 31 Dec) and eight irrigation scenarios were analysed in-silico using the crop model APSIM. For the simulations, the first four irrigation scenarios were set by applying 50%ETc during one of the four growth stages: vegetative stage, flowering stage, pod development and pod-filling stage, and maturity stage. The other five irrigation treatments were 0%ETc, 25%ETc, 50%ETc, 75%ETc, and 100%ETc throughout the growing season. Soil water content and above-ground dry matter were measured at regular time intervals. Seed yield, 100-seed weight, oil and protein contents were determined at harvest. Water deficit during pod development and pod-filling stage had significant effect on seed yield. The flowering stage was the next most sensitive stage for water deficit. During both cropping seasons, the 33% treatment yielded 51% of the fully irrigated reference. The latter had a significantly higher water productivity than all the deficit treatments. Early-sown soybean had higher yield than the late sown soybean. Sowing as late as early December was found to be still suitable for double cropping without significant yield loss. The result of this study is particularly useful for soybean farmers in water-scarce regions, such as south-eastern Australia, who practice double cropping with a tight cropping calendar.

Effects of the seedling tray overlapping for seed emergence mode on emergence characteristics and growth of rice seedlings.

Seedling mode plays a crucial role in the rice production process, as it significantly affects the growth and development of seedlings. Among the various seedling modes, the seedling tray overlapping for seed emergence mode (STOSE mode) has been demonstrated to be effective in enhancing seedling quality. However, the impact of this mode on the germination and growth of seeds with varying plumpness remains uncertain. To investigate the effect of the STOSE mode on seedling emergence characteristics, growth uniformity, and nutrient uptake of seeds with varying plumpness levels, we conducted a study using super early rice Zhongzao 39 (ZZ39) as the test material. The seeds were categorized into three groups: plumped, mixed, and unplumped. The results indicated that the STOSE mode significantly improved the seedling rate for all types of seeds in comparison to the seedling tray nonoverlapping for seed emergence mode (TSR mode). Notably, the unplumped seeds exhibited the most pronounced enhancement effect. The soluble sugar content of the seeds increased significantly after 2 days of sowing under the STOSE mode, whereas the starch content exhibited a significant decrease. Furthermore, the STOSE mode outperformed the TSR mode in several aspects including seedling growth uniformity, aboveground dry matter mass, root traits, and nutrient uptake. Overall, the STOSE mode not only promoted the germination and growth of plumped and mixed seeds but also had a more pronounced impact on unplumped seeds.

Spacing of subsurface poultry litter bands: Influence on maize performance and nitrogen use efficiency

AbstractPoultry litter (PL) is traditionally surface broadcast to no‐till maize (Zea mays L.). PL is nutrient‐dense, and surface‐applied PL nitrogen (N) is vulnerable to losses to the atmosphere and water systems. An application method was developed by USDA‐ARS scientists for shallow subsurface banding PL to reduce ammonia (NH3) volatilization and surface runoff. There is limited information on how this application method will affect conservation and nutrient accessibility in no‐till maize. The objectives were to determine if adjusting PL lateral subsurface band placement in relation to maize rows affects nutrient use and maize yields. Treatments were a nontreated control (NTC), urea ammonium nitrate surface banded (Fert), poultry litter surface broadcast (PLBr), and three subsurface banded PL treatments. The subsurface PL treatments were one (PLSub1), two (PLSub2), or three (PLSub3) bands between maize rows. Treatments receiving N were applied at 180 kg total N ha−1. Nitrogen concentration in V4 aboveground dry matter was higher in PLSub1 than PLSub2. Aboveground dry matter yields for all PLSub treatments were greater than PLBr and comparable to Fert. The PLSub1 and PLSub2 treatments resulted in maize grain yields equivalent to Fert and greater than PLBr and NTC when averaged across years. Few differences were observed in postharvest soil sample nutrient concentrations between PLSub treatments. These results suggest that subsurface banding PL can conserve N and increase no‐till maize yield over traditional surface broadcast PL; however, increasing the frequency of subsurface PL bands did not clearly affect nutrient conservation or accessibility to the maize.

Nutrient and growth elucidation of a novel coated urea on oilseed rape in three main cultivation areas

A novel coated urea (MVCU) was prepared, and its application effect was verified by field trials of oilseed rape in three main cultivation areas. Meanwhile, the nutrient release and coating layer changes of MVCU in static water at 25 °C and different soils were systematically evaluated. MVCU showed a long nutrient release time under static water (77 days) and soil incubation (140 days) conditions due to the slow degradation of the coating layer in MVCU, and its nitrogen release coincided well with oilseed rape nitrogen demand. The above results were further confirmed by FT-IR spectra and SEM analysis. Compared with conventional urea (U), the field trials of MVCU in the three main cultivation areas showed high nitrogen utilization efficiency and yield advantages in oilseed rape. The field trials results indicated that the MVCU significantly enhanced the aboveground dry matter (28.7%), the seed nitrogen concentration (9.5%) and aboveground nitrogen accumulation (42.5%) of oilseed rape at the mature stage as compared to that of the U. The oilseed rape yield enhanced by 932.8 kg/hm2, the average growth rate was 65.1%, and nitrogen utilization efficiency increased by 21.2%. In short, MVCU has the advantages of excellent slow-release performance and strong applicability, and its yield-increasing effect on oilseed rape could reach or even be better than that of traditional fertilization.

Combining Recurrent Neural Network and Sigmoid Growth Models for Short-Term Temperature Forecasting and Tomato Growth Prediction in a Plastic Greenhouse

Compared with open-field cultivation, greenhouses can provide favorable conditions for crops to grow through environmental control. The prediction of greenhouse microclimates is a way to reduce environmental monitoring costs. This study used several recurrent neural network models, including long short-term memory (LSTM), gated recurrent unit, and bi-directional LSTM, with varying numbers of hidden layers and units, to establish a temperature forecasting model for a plastic greenhouse. To assess the generalizability of the proposed model, the most accurate forecasting model was used to predict the temperature in a greenhouse with different specifications. During a test period of four months, the best proposed model’s R2, MAPE, and RMSE values were 0.962, 3.216%, and 1.196 °C, respectively. Subsequently, the outputs of the temperature forecasting model were used to calculate growing degree days (GDDs), and the predicted GDDs were used as an input variable for the sigmoid growth models to simulate the leaf area index, fresh fruit weight, and aboveground dry matter of tomatoes. The R2 values of the growth model for the three growth traits were all higher than 0.80. Moreover, the fitted values and the parameter estimates of the growth models were similar, irrespective of whether the observed GDD (calculated using the actual observed data) or the predicted GDD (calculated using the temperature forecasting model output) was used. These results indicated that the proposed temperature forecasting model could accurately predict the temperature changes inside a greenhouse and could subsequently be used for the growth prediction of greenhouse tomatoes.

More N fertilizer, more maize, and less alfalfa: maize benefits from its higher N uptake per unit root length.

Root plasticity is fundamental to soil nutrient acquisition and maximizing production. Different soil nitrogen (N) levels affect root development, aboveground dry matter accumulation, and N uptake. This phenotypic plasticity is well documented for single plants and specific monocultures but is much less understood in intercrops in which species compete for the available nutrients. Consequently, the study tested whether the plasticity of plant roots, biomass and N accumulation under different N levels in maize/alfalfa intercropping systems differs quantitatively. Maize and alfalfa were intercropped for two consecutive years in large soil-filled rhizoboxes and fertilized with 6 different levels of N fertilizer (0, 75, 150, 225, 270, and 300 kg ha-1). Root length, root surface area, specific root length, N uptake and yield were all increased in maize with increasing fertilizer level, whereas higher N rates were supraoptimal. Alfalfa had an optimal N rate of 75-150 kg ha-1, likely because the competition from maize became more severe at higher rates. Maize responded more strongly to the fertilizer treatment in the second year when the alfalfa biomass was much larger. N fertilization contributes more to maize than alfalfa growth via root plasticity responses. Our results suggest that farmers can maximize intercropping yield and economic return by optimizing N fertilizer management.

Molecular and biochemical responses of sesame (Sesame indicum L.) to rhizobacteria inoculation under water deficit.

Water scarcity is a challenge for sesame cultivation under rainfed conditions. In this scenario, a potential strategy to alleviate the water deficit is the application of plant growth-promoting bacteria. The objective of this study was to analyze the interaction of rhizobacteria with sesame cultivation under water deficit conditions. An experiment was conducted in pots in a greenhouse using the BRS Morena sesame cultivar. The experimental design was completely randomized in a factorial scheme: 2 (irrigation regimes - daily irrigation and water deficit by suspending irrigation until 90% stomatal closure) x 6 (treatments with nitrogen or inoculants), with 5 replications. The types of fertilization were characterized by the addition of nitrogen (ammonium sulfate; 21% N), inoculants based on Bacillus spp. (pant001, ESA 13, and ESA 402), Agrobacterium sp. (ESA 441), and without nitrogen (control). On the fifth day after the suspension of irrigation, plant material was collected for gene expression analysis (DREB1 and HDZ7), activities of antioxidant enzymes (superoxide dismutase and catalase), relative proline content, and photosynthetic pigments. At the end of the crop cycle (about 85 days), production characteristics (root dry matter, aboveground dry matter, number of capsules, and thousand seed weight), as well as leaf nitrogen (N) and phosphorus (P) content, were evaluated. There was a positive effect on both production and biochemical characteristics (proline, superoxide dismutase, catalase, and photosynthetic pigments). Regarding gene expression, most of the inoculated treatments exhibited increased expression of the DREB1 and HDZ7 genes. These biological indicators demonstrate the potential of rhizobacteria for application in sesame cultivation, providing nutritional supply and reducing the effects of water deficit.

Effects of climactic warming on the starch and protein content of winter wheat grain under conservation tillage in the North China Plain

Climate warming is expected to affect global food security and nutritional quality, particularly winter wheat grain protein content. No-tillage (NT) agriculture may be an effective option to mitigate the effects of climate warming; however, the associated mechanism remains unclear. Therefore, this study investigated the effects of warming under NT and conventional tillage (CT) treatments on the physiological growth processes, yield, yield components, plant nitrogen metabolism, as well as grain protein content and fractions of winter wheat in the North China Plain for four consecutive years (2021–2022). The results showed that temperature increases under the NT and CT systems significantly impacted winter wheat growth and development, prolonged the effective reproductive period, and increased the leaf area index, photosynthesis rate, and aboveground dry matter mass in the pre-flowering stage. Hence, the temperature increase and tillage treatment affected the components and yield of winter wheat. The number of fruiting spikelets decreased significantly, and the number of grains and thousand-grain weight increased under the CT and NT systems. Meanwhile, the elevated temperature significantly increased the winter wheat yield by 11.4% (CT) and 62.3% (NT) compared with the control group. Temperature increases also significantly increased winter wheat seed protein content by 10.88% and 30.91% under CT and NT, respectively. The effects of warming and tillage treatments on seed protein fractions were more complex, with warming under CT reducing the albumin, globulin, and glutenin contents, whereas warming under NT increased the contents of all four protein fractions. This study provides a scientific basis for the mechanism underlying climate warming effects on protein content and fractions of winter wheat grains.

Yield and dry matter production of soybean response to late planting in southwestern Japan

ABSTRACT The selection of the sowing date is one of the most important decisions in soybean production. It is important for farmers to know the expected seed yield when developing a sowing plan. The objective of this study was to quantitatively reveal the decreased seed yield ratio during late sowing in southwestern Japan under irrigated conditions. Total above ground dry matter and distribution were measured from July to August sowing in 2018 and 2019 in Fukuyama, Hiroshima, Japan. The harvest index in the August sowing did not decrease compared to the July sowing under irrigated conditions. The decrease in yield was related to the total aboveground dry matter rather than to the harvest index. The decrease in total aboveground dry matter was related to the total amount of solar radiation intercepted rather than to radiation use efficiency. A significant regression equation was obtained for the relative yield, which was calculated from the maximum seed yield observed from early to mid-July. When seeds were sown after mid-July, our result showed that the seed yield will decrease by 0.60% per day for Sachiyutaka A1 and by 0.64% for Akimaro, even under conditions of 100% seedling establishment and controlled soil water conditions. This regression equation can be used in fields as an indicator of seed yield where irrigation is possible.

Effects of Low Light after Heading on the Yield of Direct Seeding Rice and Its Physiological Response Mechanism.

As a photophilous plant, rice is susceptible to low-light stress during its growth. The Sichuan Basin is a typical low-light rice-producing area. In this study, eight rice varieties with different shade tolerances were studied from 2021 to 2022. The physiological adaptability and yield formation characteristics of rice were studied with respect to photosynthetic physiological characteristics and dry matter accumulation characteristics, and the response mechanism of rice to low light stress was revealed. The results showed that the shading treatment significantly increased the chlorophyll a, chlorophyll b, and total chlorophyll contents in the leaves of direct-seeded rice after heading, and the total chlorophyll content increased by 1.68-29.70%. Nitrate reductase (NR) activity first increased and then decreased under each treatment, and the shading treatment reduced the NR activity of direct-seeded rice. Compared to the control treatment, the peroxidase (POD) activity of each variety increased from 7 to 24 d after the shading treatment. The transketolase (TK) activity in direct-seeded hybrid rice increased under low light stress. Compared with the control, shading treatment significantly reduced the aboveground dry matter, grain number per panicle, and seed setting rate of direct-seeded rice at the full heading stage and maturity stage, thus reducing the yield of direct-seeded rice by 26.10-34.11%. However, under the shading treatment, Zhenliangyou 2018 and Jingliangyou 534 maintained higher chlorophyll content and related enzyme activities, accumulated more photosynthetic products, and reduced yield. In general, Zhenliangyou 2018 and Jingliangyou 534 still had a yield of 7.06-8.33 t·hm-2 under low light. It indicated that Zhenliangyou 2018 and Jingliangyou 534 had better stability and stronger tolerance to weak light stress and had a higher yield potential in weak light areas such as Sichuan.

Ground Cover Rice Production System Affects Soil Water, Nitrogen Dynamics and Crop Growth Differentially with or without Climate Stress.

The ground cover rice production system (GCRPS) has been proposed as a potential solution to alleviate seasonal drought and early low-temperature stress in hilly mountainous areas; clarifying its impact on crop growth is crucial to enhance rice productivity in these areas. A two-year (2021-2022) field experiment was conducted in the hilly mountains of southwest China to compare the effects of the traditional flooding paddy (Paddy) and GCRPS under three different nitrogen (N) management practices (N1, zero-N fertilizer; N2, 135 kg N ha-1 as a urea-based fertilizer; and N3, 135 kg N ha-1 with a 3:2 base-topdressing ratio as urea fertilizer for the Paddy or a 1:1 basal application ratio as urea and manure for GCRPS) on soil water storage, soil mineral N content and crop growth parameters, including plant height, tiller numbers, the leaf area index (LAI), aboveground dry matter (DM) dynamics and crop yield. The results showed that there was a significant difference in rainfall between the two growth periods, with 906 mm and 291 mm in 2021 and 2022, respectively. While GCRPS did not significantly affect soil water storage, soil mineral N content, and plant height, it led to a reduction in partial tiller numbers (1.1% to 31.6%), LAI (0.6% to 20.4%), DM (4.4% to 18.8%), and crop yield (7.4% to 22.0%) in 2021 (wet year) compared to the Paddy. However, in 2022 (dry year), GCRPS led to an increase in tiller numbers (13.7% to 115.4%), LAI (17.3% to 81.0%), DM (9.0% to 62.6%), and crop yield (2.9% to 9.2%) compared to the Paddy. Structural equation modeling indicated that GCRPS significantly affected tiller numbers, plant height, LAI, DM, and productive tiller numbers, which indirectly influenced crop yield by significantly affecting tiller numbers and productive tiller numbers in 2022. Overall, the effects of GCRPS on soil water and N dynamics were not significant. In 2021, with high rainfall, no drought, and no early, low-temperature stress, the GCRPS suppressed crop growth and reduced yield, while in 2022, with drought and early low-temperature stress and low rainfall, the GCRPS promoted crop growth and increased yield, with tiller numbers and productive tiller numbers being the key factors affecting crop yield.

Irrigation depth and nitrogen rate effects on seed cotton yield, fiber quality and water-nitrogen utilization efficiency in southern Xinjiang, China

Seed cotton yield and fiber quality are two primary factors that influence the international competitiveness of cotton. To enhance the water-nitrogen utilization efficiency and promote the sustainable cotton production, field experiments were performed in 2020 and 2021 to explore the effects of irrigation depth and nitrogen (N) fertilization rate on N uptake and distribution, seed cotton yield, fiber quality traits and water-nitrogen utilization efficiency in the Korla region of southern Xinjiang, China. Three irrigation depths (W1: 60% ETc, W2: 80% ETc, W3: 100% ETc; ETc was crop water consumption) and four N rates (N0: 0 kg ha−1, N200: 200 kg ha−1, N300: 300 kg ha−1, N400: 400 kg ha−1) were applied. The results showed irrigation depth and N rate significantly influenced N uptake and distribution in plant organs, seed cotton yield, crop water productivity (WP), partial factor productivity of nitrogen (PFPN) and some fiber quality traits. Increasing irrigation depth improved plant height, leaf area index, aboveground dry matter and seed cotton yield, while increasing N rate increased and then declined these indicators. At the squaring and flowering stages, the N accumulation in all parts of cotton increased as irrigation depth and N rate increased, whereas it increased and then declined with increasing N rate at the boll-setting and harvesting stages. At the squaring and flowering stages, N was mainly accumulated in the leaves. As the growth period progressed, N was transported to bolls and the proportion of N content in leaves decreased. The proportion of N accumulation in cotton bolls was largest at the boll-setting and harvesting stages, and the N accumulation in plant organs followed the order of boll > leaf > stem > root. As irrigation depth increased, PFPN increased but WP decreased. As N rate increased, PFPN decreased but WP increased and then declined. The increases in N rate improved fiber quality. The maximum seed cotton yield (7578 kg ha−1 in 2020 and 7173 kg ha−1 in 2021) and greater WP, PFPN and fiber quality occurred in W3N300, which was recommended as a sustainable cotton production strategy in the Korla region of southern Xinjiang and elsewhere with similar environments to improve water-nitrogen utilization efficiency, seed cotton yield and alleviate soil nitrate pollution risk.

QTL mapping of nitrogen use efficiency traits at the seedling and maturity stages under different nitrogen conditions in barley (Hordeum vulgare L.)

AbstractNitrogen (N) is an essential element for plant growth and development. The identification and utilization of N use efficiency (NUE) loci are essential for breeding high NUE cultivars. In this study, 15 NUE traits were measured in a recombinant inbred line population containing 121 lines derived from the cross between a cultivated barley (Baudin) and a wild barley (CN4027). The hydroponic culture was conducted with normal N and low N treatments in one‐time frame, and field trials were conducted with N sufficiency and N deficiency treatments in two growing seasons. Twenty‐two quantitative trait loci (QTLs) and four clusters were detected. Of them, the five stable QTLs Qgna.sau‐3H for grain N concentration, Qtna.sau‐3H for total N accumulation per plant, Qnhi.sau‐3H for N harvest index, Qnutegy.sau‐3H for N utilization efficiency for grain yield and Qanutedm.sau‐3H.1 for N utilization efficiency for aboveground dry matter were co‐located on chromosome 3H flanked by the markers bpb6282426 and bpb4786261. These two novel QTL clusters simultaneously controlled NUE traits at the seedling and maturity stages. Some genes related to NUE traits in intervals of the major QTLs were predicted. The significant relationships between NUE traits and agronomic and physiological traits were detected and discussed. In conclusion, this study uncovers the most promising genomic regions for the marker‐assisted selection of NUE traits to improve NUE in barley.

Optimizing Nitrogen Fertilization to Enhance Productivity and Profitability of Upland Rice Using CSM-CERES-Rice.

Nitrogen (N) deficiency can limit rice productivity, whereas the over- and underapplication of N results in agronomic and economic losses. Process-based crop models are useful tools and could assist in optimizing N management, enhancing the production efficiency and profitability of upland rice production systems. The study evaluated the ability of CSM-CERES-Rice to determine optimal N fertilization rate for different sowing dates of upland rice. Field experimental data from two growing seasons (2018-2019 and 2019-2020) were used to simulate rice responses to four N fertilization rates (N30, N60, N90 and a control-N0) applied under three different sowing windows (SD1, SD2 and SD3). Cultivar coefficients were calibrated with data from N90 under all sowing windows in both seasons and the remaining treatments were used for model validation. Following model validation, simulations were extended up to N240 to identify the sowing date's specific economic optimum N fertilization rate (EONFR). Results indicated that CSM-CERES-Rice performed well both in calibration and validation, in simulating rice performance under different N fertilization rates. The d-index and nRMSE values for grain yield (0.90 and 16%), aboveground dry matter (0.93 and 13%), harvest index (0.86 and 7%), grain N contents (0.95 and 18%), total crop N uptake (0.97 and 15%) and N use efficiencies (0.94-0.97 and 11-15%) during model validation indicated good agreement between simulated and observed data. Extended simulations indicated that upland rice yield was responsive to N fertilization up to 180 kg N ha-1 (N180), where the yield plateau was observed. Fertilization rates of 140, 170 and 130 kg N ha-1 were identified as the EONFR for SD1, SD2 and SD3, respectively, based on the computed profitability, marginal net returns and N utilization. The model results suggested that N fertilization rate should be adjusted for different sowing windows rather than recommending a uniform N rate across sowing windows. In summary, CSM-CERES-Rice can be used as a decision support tool for determining EONFR for seasonal sowing windows to maximize the productivity and profitability of upland rice production.

Wheat cultivar replacement drives soil microbiome and microbial cooccurrence patterns

While wheat domestication is reported to influence the soil microbial community, few studies have evaluated the influence of cultivar replacement in modern breeding on both bacterial and fungal communities. Especially, few studies reported the bacterial-fungal interkingdom association by analysis of taxa co-occurrence or co-exclusion between different wheat growth stages. In this study, we selected major wheat cultivars from different decades to investigate their genetic relatedness, plant traits, soil bacterial and fungal communities in the rhizosphere and proximal root zone, and the relationships between them. Our results indicated that host selection had the greatest impact on bacterial and fungal communities compared to growth stage and sampling location (P<0.001). At flowering, the soil microbial community in the genotype group consisting of the 1950 s (W50 s) and 1960 s (W60 s) cultivars could be clearly distinguished from those in later genotype groups. Plant traits explained the largest source of variation in microbial β-diversity (12.8–20.6%) (P=0.01), with plant height, aboveground dry matter, leaf area per plant and specific root length being associated with the divergence in microbial composition or quantity among cultivars. The cultivar from the 1970 s (W70 s) enriched a greater number of microbial taxa with the highest relative abundance, suggesting that old cultivar could be considered as a source of cultivar-microbe interaction. The cultivar from the 2000 s (W00 s) enriched taxa from the bacterial genus Nocardioides and increased the fungal phylum Glomeromycota in the rhizosphere. At three growth stages, W00 s root-zone exhibited the highest bacteria/fungi ratio (B/F) and contained more phosphorus cycle-related bacterial phoD-genes than W50 s and W60 s. The co-occurrence network revealed more operational taxonomic units (OTUs) from the bacterial order Rhizobiales in the largest module of W00 s. The increased B/F ratio and the aforementioned taxa are reported to be involved in soil nitrogen and phosphorus availability, suggesting that contemporary cultivar may recruit beneficial bacteria and fungi while weaken the association with other fungi. These findings contribute to the development of microbiome-based breeding strategies for sustainable wheat farming.

Enhancing maize yield through understanding the novel shoot-root interaction in morphology among hybrids with dense planting

ContextUnderstanding the shoot-root characteristics and their interaction of maize is essential to break the constraints of the densification process and improve grain yield. ObjectiveThe objective of the work was to study the interaction between the above-ground canopy and below-ground root system in morphology and its relationship to grain yield in dense planting with different hybrids. MethodsThis study conducted a 2-yr field experiment with three modern hybrids (JNK728, ZD958 and XY335) at the Wuqiao Experimental Station in Northern China. ResultsAmong hybrids, XY335 attained the highest grain yield of 14,886.9 kg hm−2 in 2019 and 10,078.8 kg hm−2 in 2020 with a density of 7.5 × 104 plants hm−2. For the shoot at the silking stage (R1), the lowest leaf orientation value for both middle and upper leaves and ear-to-height ratio among three hybrids were found in XY335 with the compact plant phenotype. Meanwhile, the highest photosynthesis rate of ear leaves (33.0 umol m2˙s−1) at R1 was also observed in XY335. At physiological maturity (R6), the above-ground dry matter (AGDM) was 4.6%− 10.4% higher in XY335 than the other two hybrids. For the root system at both R1 and R6 with the density of 7.5 × 104 plants hm−2, the highest value for root system indicators in morphology such as root total length (RL), root surface area (RSA), root volume (RV) was observed in XY335. From R1 to R6, RL, RSA and RV in XY335 averaged 24,749.6 cm, 3486.8 cm2, 51.5 cm3, 1.3–14.6% higher than JNK728, and 10.2–23.9% higher than ZD958, respectively. Furthermore, the lower senescence of the root system was also observed in XY335, with a 22.0–32.1% lower decrease from R1 to R6 in RL, RSA, and RV compared with the other two hybrids. ConclusionsFor the shoot-root interaction, per unit decrease in morphology indicator in the root per plant with density increase of XY335 accompanied with more AGDM accumulation and thus higher grain yield. ImplicationsThe observations on shoot-root characteristics and their interaction from this study are essential to selecting a hybrid that allows a better adaptation to planting at high density, developing an effective management strategy, and breeding high-density tolerant hybrids.